CN109709794A - A kind of control method suitable for motion controller - Google Patents
A kind of control method suitable for motion controller Download PDFInfo
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- CN109709794A CN109709794A CN201811561265.3A CN201811561265A CN109709794A CN 109709794 A CN109709794 A CN 109709794A CN 201811561265 A CN201811561265 A CN 201811561265A CN 109709794 A CN109709794 A CN 109709794A
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Abstract
A kind of control method suitable for motion controller disclosed by the invention, step 1, the running track location information of executing agency's planning of motion controller, velocity and acceleration information；Step 2, the parameter of acceleration PI controller and the parameter of position PID controller are found out；Step 3, photoelectric encoder acquires the lower current location information of dynamic in real time；Velocity sensor detects real-time speed, and calculates acceleration；Step 4, the running track location information planned in step 1 is compared with the location information that step 3 acquires, obtains position PID controller output valve；Step 5, it is compared the acceleration information that position PID controller output valve and step 3 acquire to obtain its error amount, and is transported in acceleration PI controller and is handled, obtain the output quantity of acceleration PI controller；Step 6, the output quantity of acceleration PI controller inputs motor driver, and motor driver driving motor controls the running track and speed of executing agency.
Description
Technical field
The invention belongs to control method fields, are related to a kind of control method suitable for motion controller.
Background technique
With being constantly progressive for domestic industry control technology, motion control accuracy is wanted in the rapid development of robot technology
Ask higher and higher.Nowadays the domestic generally existing inaccurate coordination of motion controller, expansion and flexibility are poor, and cost performance is relatively low
The disadvantages of；Traditional control technology can no longer meet modern industry for the complexity of mechanism kinematic, stability, rapidity,
It is extremely urgent to explore more preferably control method in order to mention high control precision for the requirement of accuracy.
Summary of the invention
The purpose of the present invention is to provide a kind of control method suitable for motion controller, this method can be improved movement
The accuracy and flexibility ratio of controller executing agency.
The technical scheme adopted by the invention is that: a kind of control method suitable for motion controller specifically includes following
Step:
Step 1, the running track information that executing agency plans in motion controller is obtained by interpolation algorithm, passes through s speed
Degree curved line arithmetic obtains the velocity and acceleration information of executing agency's planning；
Step 2, position PID controller is stored it in the parameter that particle swarm optimization algorithm finds out position PID controller,
Position PID controller after being optimized,
Acceleration PI controller is stored it in the parameter that particle swarm optimization algorithm finds out acceleration PI controller, is obtained
PI controller after optimization；
Step 3, the lower current location information of dynamic is acquired in real time by photoelectric encoder；It is real-time by velocity sensor detection
Speed, and calculate acceleration；
Step 4, the running track location information planned in step 1 is compared with the location information that step 3 acquires, is obtained
To location information error amount, then location information error amount is input to after step 2 optimizes in the PID controller of position and is handled,
Obtain the output quantity of position PID controller；
Step 5, the acceleration information that position PID controller output valve and step 2 acquire will be obtained in step 4 to be compared
Its error amount is obtained, and is transported in step 2 optimization post-acceleration PI controller and is handled, obtains acceleration PI controller
Output quantity；
Step 6, the output quantity of acceleration PI controller inputs motor driver, and the control of motor driver driving motor executes
The running track and speed of mechanism.
The features of the present invention also characterized in that
It is in step 1 specifically includes the following steps:
Step 1.1, it is known that the initial point position of executing agency and terminating point position calculate execution machine using interpolation system
The running track information of structure planning；
Step 1.2, it is known that axis initial point position and terminating point position add and subtract the short-cut counting method according to s curve and determine executing agency
Planning velocity and acceleration information during whole service.
The parameter of the position PID controller found out in step 2 with particle swarm optimization algorithm specifically includes the following steps:
Step 2.1, initialization population particle scale (i.e. the number N of population particle), the number of iterations m, setting particle are initial
Position, initial velocity V0, space search range, the error being arranged between output quantity and input quantity is e (t), and to first generation grain
Son carries out pid parameter coding；
Step 2.2, it calculates and works as former generation population fitness value, find the optimum position Pbest of current particleijMost with population
Best placement Gbestj；
Step 2.2 specifically includes the following steps:
Step 2.2.1, according to the requirement of the characteristic and error of PID, the formula for choosing grade of fit function f (t) is as follows:
Wherein e (t) indicates error originated from input.
Step 2.2.2, (2) calculate particle fitness value fitness according to the following formulai:
fitnessi=f (t) | (b(k,i),b(k-1,i),b(k-2,i),...,b(1,i)) (2)；
Wherein, fitnessiIndicate the grade of fit of i-th of particle, b(i,j)Indicate i-th of particle in the position that jth is tieed up, j=
1,2,3 ... k, k indicate the maximal dimension of particle spatially；
Step 2.2.3, by initial Kp, Ki, KdValue input PID controller, obtains the error under the state, according to formula
(1), (2) calculate particle fitness value under original state, and it is maximum for current population optimum position to choose particle fitness value
Gbestj；Initial position is current particle optimum position Pbestij。
Step 2.3, the current algebra where particle is compared with step 2.1 the number of iterations m, where judging particle
Whether current algebra reaches maximum algebra, if reaching maximum algebra, goes to step 2.6 execution；Conversely, executing step 2.4；
Step 2.4, the speed and particle position of t+1 moment more new particle are calculated；
The speed of t+1 moment more new particle is calculated by formula (3):
Vi(t+1)=w × Vi((t)+C1×rand()(Pbestij-Xi(t)+C2×rand()×(Gbestj-Xi(t))
(3)
ViFor the speed of i-th of particle, PbestijThe optimum position up to the present occurred by each particle, Gbestj
The optimum position up to the present occurred by all particles, XiFor the current position of each particle, C1, C2To learn constant,
W is inertia weight, and rand () is the random number between 0~1；
Particle position is updated by formula (4) calculating t+1 moment:
Xi(t+1)=Xi(t)+Vi(t+1) (4)
Step 2.5, the particle position at t+1 moment is calculated according to step 2.4, repeats grain when step 2.2 finds t+1
The optimum position Pbest of sonijWith population optimum position Gbestj, repeat step 2.3；
Step 2.6, it is three-dimensional value that step 2.5, which calculates the moment population optimum position t+1, which respectively corresponds output
K in the PID controller of positionp、Ki、KdParameter.
The parameter of acceleration PI controller is found out in step 2 with particle swarm optimization algorithm, specific steps repeat step 2.1 and arrive
2.6, calculate the K in acceleration PI controllerp、KiParameter.
The beneficial effects of the present invention are: the control method suitable for motion controller of the invention, bent by s speed first
Line algorithm and interpolation algorithm obtain the trace information of executing agency's planning of motion controller, then will be in planned trajectory information
Standard location information and the real-time position information detected difference as input signal, be sent into PID controller and be adjusted；This
When the difference of the acceleration information of output valve and detection that adjusts of PID controller be used as the input quantity of acceleration PI controller again；?
Error can be reflected quickly using position PID controller in adjusting and processing is adjusted；Use acceleration for regulated quantity, energy
It is enough that the error being likely to occur is eliminated in time.By using particle swarm optimization algorithm, can obtain most preferred PID controller and
The parameter of PI controller makes double closed-loop control system play more excellent regulating power.One kind of the invention is suitable for movement control
Position PID controller and acceleration PI controller in the control method of device processed play vital work in feedback regulation
With its parameter selection directly decides the levels of precision of executing agency's operation.
Detailed description of the invention
Fig. 1 is a kind of process principle figure of the control method suitable for motion controller of the present invention.
Specific embodiment
The following describes the present invention in detail with reference to the accompanying drawings and specific embodiments.
The present invention provides a kind of control methods suitable for motion controller, as shown in Figure 1, including walking in detail below
It is rapid:
Step 1, the running track information of executing agency's planning is obtained by interpolation algorithm, is obtained by s rate curve algorithm
The velocity and acceleration information planned to executing agency；
It is in step 1 specifically includes the following steps:
Step 1.1, it is known that the initial point position of executing agency and terminating point position calculate execution machine using interpolation system
The running track information of structure planning.Current mainstream arc interpolation --- B-spline Curve interpolation is used in this secondary design
Algorithm.
Step 1.2, it is known that axis initial point position and terminating point position add and subtract the short-cut counting method according to s curve and determine executing agency
Planning velocity and acceleration information during whole service.
Step 2, position PID controller is stored it in the parameter that particle swarm optimization algorithm finds out position PID controller,
Position PID controller after being optimized,
Acceleration PI controller is stored it in the parameter that particle swarm optimization algorithm finds out acceleration PI controller, is obtained
PI controller after optimization；
The parameter of the position PID controller found out in step 2 with particle swarm optimization algorithm specifically includes the following steps:
Step 2.1, initialization population particle scale (i.e. the number N of population particle), the number of iterations m, setting particle are initial
Particle initial velocity V is arranged in position0With space search range, the error being arranged between output quantity and input quantity is e (t), and right
First generation particle carries out pid parameter coding；
Step 2.2, it calculates and works as former generation population fitness value, find the optimum position Pbest of current particleijMost with population
Best placement Gbestj；
Step 2.2.1, according to the requirement of the characteristic and error of PID, the formula for choosing grade of fit function f (t) is as follows:
Wherein e (t) indicates error originated from input.
Step 2.2.2, (2) calculate particle fitness value fitness according to the following formulai:
fitnessi=f (t) | (b(k,i),b(k-1,i),b(k-2,i),...,b(1,i)) (2)；
Wherein, fitnessiIndicate the grade of fit of i-th of particle, b(i,j)Indicate i-th of particle in the position that jth is tieed up, j=
1,2,3 ... k, k indicate the maximal dimension of particle spatially；
Step 2.2.3, by initial Kp, Ki, KdValue input PID controller, obtains the error under the state, according to formula
(1), (2) calculate particle fitness value under original state, and it is maximum for current population optimum position to choose particle fitness value
Gbestj；Initial position is current particle optimum position Pbestij；
Step 2.3, the current algebra where particle is compared with step 2.1 the number of iterations m, where judging particle
Whether current algebra reaches maximum algebra, if reaching maximum algebra, goes to the execution of step 2.6 step；Conversely, executing step 2.4；
Step 2.4, the speed and particle position of t+1 moment more new particle are calculated；
The speed of t+1 moment more new particle is calculated by formula (3):
Vi(t+1)=w × Vi((t)+C1×rand()(Pbestij-Xi(t)+C2×rand()×(Gbestj-Xi(t))
(3)
ViFor the speed of i-th of particle, PbestijThe optimum position up to the present occurred by each particle, Gbestj
The optimum position up to the present occurred by all particles, XiFor the current position of each particle, C1, C2To learn constant,
W is inertia weight, and rand () is the random number between 0~1；
Particle position is updated by formula (4) calculating t+1 moment:
Xi(t+1)=Xi(t)+Vi(t+1) (4)
Step 2.5, the particle position at t+1 moment is calculated according to step 2.4, repeats grain when step 2.2 finds t+1
The optimum position Pbest of sonijWith population optimum position Gbestj, repeat step 2.3；
Step 2.6, it is three-dimensional value that step 2.5, which calculates the moment population optimum position t+1, which respectively corresponds output
K in the PID controller of positionp、Ki、KdParameter；
The parameter of acceleration PI controller is found out in step 2 with particle swarm optimization algorithm, specific steps repeat step 2.1 and arrive
2.6, calculate the K in acceleration PI controllerp、KiParameter.
Step 3, the lower current location information of dynamic is acquired in real time by photoelectric encoder；It is real-time by velocity sensor detection
Speed, and calculate acceleration；
Step 4, the running track location information planned in step 1 is compared with the location information that step 3 acquires, is obtained
It is handled to location information error amount, then by location information error amount input position PID controller, obtains position PID control
Device output valve；
Step 5, the acceleration information that position PID controller output valve and step 3 acquire will be obtained in step 4 to be compared
Its error amount is obtained, and is transported in acceleration PI controller and is handled, obtains the output quantity of acceleration PI controller；
Step 6, the output quantity of acceleration PI controller inputs motor driver, and the control of motor driver driving motor executes
The running track and speed of mechanism.
Comparative example:
Traditional PID controller:
Traditional PID control system mainly has analog pid controller and controlled device two parts to constitute, and is a kind of Linear Control
Device.Control by the difference of preset value and real output value as system inputs, and ratio, integral in PID, differential parameter are all
Fixed；Its control law can be described as following formula:
Major parameter has Kp、Ki、KdDeng Kp、Ki、KdEffect are as follows:
(1) proportional component Kp: proportionally reflect the deviation signal e (t) of control system, deviation once generates, controller
Control action is generated immediately, reduces deviation.
(2) integral element Ki: be mainly used for eliminate static difference, improve system without margin；The power of integral action depends on
Integration time constant T1, T1Bigger, integral action is weaker, conversely, then stronger.
(3) differentiation element Kd: reflect the variation tendency (rate of change) of deviation signal, and can be become too big in deviation signal
Before, an effective early stage revise signal is introduced in systems, to accelerate the movement speed of system, reduces regulating time.
Compared with control method suitable for the motion controller of the invention control method traditional with comparative example:
For the characteristic of motion controller, control method of the invention is while having continued to use traditional PID control, for control
Characteristic in the executing agency of device processed has done combination and improvement, and executing agency is made to have better tracking performance, and operation accuracy has
Very big raising.This control method uses acceleration+positioner Dual-loop feedback control mode, and accelerator feedback is produced in deviation
Controlled before life, position feedback is adjusted controller after generating deviation in time, passes through acceleration and speed variables
The adjusting of information keeps the operation of executing agency more accurate and reliable.The mode of accelerator feedback is added in traditional feedback system,
Since acceleration is the variable for influencing the next movement velocity of executing agency, this design is same real-time adjustment operation acceleration
When, also controlled before executing agency's speed deviations predetermined speed, there is the executing agency of prevention in advance to deviate expected path
Effect.In view of the Variation Features of acceleration itself, PI controller has been used, can reach better in the control method of the invention
Control effect.To ensure that executing agency can precisely run, it is provided with position feedback link, if executing agency is rubbed due to machinery
It wipes, inertia is big or other extraneous factors cause executing agency to have deviation, position feedback link with anticipated path position
Position PID controller can generate effect, the operation conditions of timely executing agency reduces error.The parameter of traditional PID control is set
It sets mainly by experience and testing and debugging, relies on experienced designer, and process is complicated, parameter tuning result also has much not
Certainty, PID controller of the present invention have used particle swarm optimization algorithm to adjust its parameter in design, and particle swarm algorithm can search for
The optimized parameter of PID controller can also obtain the optimal value of the parameter of PID while saving manpower.
By the above-mentioned means, a kind of control method suitable for motion controller of the invention, passes through s rate curve first
Algorithm and interpolation algorithm obtain the trace information of executing agency's planning of controller, then by the standard in planned trajectory information
The difference of location information and the real-time position information detected is sent into PID controller and is adjusted as input signal；PID at this time
The difference of the acceleration information of output valve and detection that controller is adjusted is used as the input quantity of acceleration PI controller again；In adjusting
Error can be reflected quickly using position PID controller and processing is adjusted；Use acceleration for regulated quantity, it can be can
The error that can occur eliminates in time.By using particle swarm optimization algorithm, most preferred PID controller and PI control can be obtained
The parameter of device makes double closed-loop control system play more excellent regulating power.It is of the invention a kind of suitable for motion controller
Position PID controller and acceleration PI controller in control method play vital position in feedback regulation, it
Parameter selection directly decides the levels of precision of executing agency's operation.The present invention is by the way of double-closed-loop control to executing agency
The precision of operation is adjusted, and can be reduced the original systematic error of controller, be improved the running precision of executing agency, make execution machine
Structure operation is more flexible.
Claims (5)
1. a kind of control method suitable for motion controller, which is characterized in that specifically includes the following steps:
Step 1, the running track information of executing agency's planning of motion controller is obtained by interpolation algorithm, it is bent by s speed
Line algorithm obtains the velocity and acceleration information of executing agency's planning；
Step 2, position PID controller is stored it in the parameter that particle swarm optimization algorithm finds out position PID controller, obtained
Position PID controller after optimization,
Acceleration PI controller is stored it in the parameter that particle swarm optimization algorithm finds out acceleration PI controller, is optimized
PI controller afterwards；
Step 3, the lower current location information of dynamic is acquired in real time by photoelectric encoder；Speed in real time is detected by velocity sensor
Degree, and calculate acceleration；
Step 4, the running track location information planned in step 1 is compared with the location information that step 3 acquires, is obtained in place
Confidence ceases error amount, then location information error amount is input to after step 2 optimizes in the PID controller of position and is handled, and obtains
The output quantity of position PID controller；
Step 5, the acceleration information that position PID controller output valve and step 2 acquire will be obtained in step 4 to be compared to obtain
Its error amount, and be transported in step 2 optimization post-acceleration PI controller and handled, obtain the output of acceleration PI controller
Amount；
Step 6, the output quantity of acceleration PI controller inputs motor driver, and motor driver driving motor controls executing agency
Running track and speed.
2. a kind of control method suitable for motion controller as described in claim 1, which is characterized in that in the step 1
Specifically includes the following steps:
Step 1.1, it is known that the initial point position of executing agency and terminating point position calculate executing agency using interpolation system and advise
The running track information drawn；
Step 1.2, it is known that axis initial point position and terminating point position add and subtract the short-cut counting method according to s curve and determine motion controller
Planning velocity and acceleration information during executing agency's whole service.
3. a kind of control method suitable for motion controller as described in claim 1, which is characterized in that in the step 2
The parameter of the position PID controller found out with particle swarm optimization algorithm specifically includes the following steps:
Step 2.1, particle initial position is arranged in initialization population particle scale (i.e. the number N of population particle), the number of iterations m,
Particle initial velocity V is set0With space search range, the error being arranged between output quantity and input quantity is e (t), and to first
Pid parameter coding is carried out for particle；
Step 2.2, it calculates and works as former generation population fitness value, find the optimum position Pbest of current particleijWith population optimum bit
Set Gbestj；
Step 2.3, the current algebra where particle is compared with step 2.1 the number of iterations m, is judged current where particle
Whether algebra reaches maximum algebra, if reaching maximum algebra, goes to step 2.6 execution；Conversely, executing step 2.4；
Step 2.4, the speed and particle position of t+1 moment more new particle are calculated；
The speed of t+1 moment more new particle is calculated by formula (3):
Vi(t+1)=w × Vi((t)+C1×rand()(Pbestij-Xi(t)+C2×rand()×(Gbestj-Xi(t)) (3)
ViFor the speed of i-th of particle, PbestijThe optimum position up to the present occurred by each particle, GbestjFor institute
There are up to the present optimum position that particle occurs, XiFor the current position of each particle, C1, C2To learn constant, w is
Inertia weight, rand () are the random number between 0~1；
Particle position is updated by formula (4) calculating t+1 moment:
Xi(t+1)=Xi(t)+Vi(t+1) (4)
Step 2.5, the particle position at t+1 moment is calculated according to step 2.4, repeats particle when step 2.2 finds t+1
Optimum position PbestijWith population optimum position Gbestj, repeat step 2.3；
Step 2.6, it is three-dimensional value that step 2.5, which calculates the moment population optimum position t+1, which respectively corresponds output position
K in PID controllerp、Ki、KdParameter.
4. a kind of control method suitable for motion controller as claimed in claim 3, which is characterized in that the step 2.2
Specifically includes the following steps:
Step 2.2.1, according to the requirement of the characteristic and error of PID, the formula for choosing grade of fit function f (t) is as follows:
Wherein e (t) indicates error originated from input.
Step 2.2.2, (2) calculate particle fitness value fitness according to the following formulai:
fitnessi=f (t) | (b(k,i),b(k-1,i),b(k-2,i),...,b(1,i)) (2)；
Wherein, fitnessiIndicate the grade of fit of i-th of particle, b(i,j)Indicate i-th of particle in the position that jth is tieed up, j=1,2,
3 ... k, k indicate the maximal dimension of particle spatially；
Step 2.2.3, by initial Kp, Ki, KdValue input PID controller, obtains the error under the state, according to formula (1), (2)
Particle fitness value under original state is calculated, and it is maximum for current population optimum position Gbest to choose particle fitness valuej；
Initial position is current particle optimum position Pbestij。
5. a kind of control method suitable for motion controller as claimed in claim 2, which is characterized in that in the step 2
The parameter of acceleration PI controller is found out with particle swarm optimization algorithm, specific steps repeat step 2.1 to 2.6, calculate acceleration
K in PI controllerp、KiParameter.
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